Since in networks the degree of nodes are distributed heterogeneously, one can exploit this fact to devise new physically meaningful removal strategies, such as targeting nodes from higher to lower degree [1]}, [2]}. These interventions on the networks are called attacks, since they are intentionally performed using some a priori information. Studying percolation based on degree attacks elucidates the role played by large degree nodes, the hubs, on the network robustness. For instance, graphs with long-tailed degree distributions are very weak to hub removal, that is, by removing a very small number of hubs the network is broken in many small components. This has catastrophic consequences for the security of real-world networks, since many of them display such degree distributions [3]}.
